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Life Expectancy Prediction using Machine Learning. This project analyzes global health, economic, and social indicators from 193 countries to identify key factors affecting life expectancy and build accurate prediction models using XGBoost and other regressors.
Laptop Price Prediction using Machine Learning. This project analyzes laptop specifications like RAM, CPU, storage, and GPU to predict prices using data preprocessing, EDA, and a Linear Regression model.
Cybersecurity threat detection project that analyzes AWS CloudWatch web traffic logs to identify suspicious and anomalous interactions using machine learning models like Isolation Forest, Random Forest, and Neural Networks.
Google Play Store App Data Analysis using Python. This project performs exploratory data analysis (EDA) to uncover trends in app categories, installs, ratings, reviews, and user engagement to help understand factors behind app success.
Coca-Cola Stock Analysis & Price Prediction using Python and Machine Learning. This project performs exploratory data analysis (EDA), technical indicator creation, and uses a Random Forest model to forecast future stock prices based on historical market data.
Uber Trip Demand Analysis and Prediction using Python and Machine Learning. This project explores trip patterns, peak demand times, and uses models like Random Forest, GBRT, and XGBoost to forecast ride demand.
Repositories
19Life Expectancy Prediction using Machine Learning. This project analyzes global health, economic, and social indicators from 193 countries to identify key factors affecting life expectancy and build accurate prediction models using XGBoost and other regressors.
Laptop Price Prediction using Machine Learning. This project analyzes laptop specifications like RAM, CPU, storage, and GPU to predict prices using data preprocessing, EDA, and a Linear Regression model.
Cybersecurity threat detection project that analyzes AWS CloudWatch web traffic logs to identify suspicious and anomalous interactions using machine learning models like Isolation Forest, Random Forest, and Neural Networks.
Google Play Store App Data Analysis using Python. This project performs exploratory data analysis (EDA) to uncover trends in app categories, installs, ratings, reviews, and user engagement to help understand factors behind app success.
Coca-Cola Stock Analysis & Price Prediction using Python and Machine Learning. This project performs exploratory data analysis (EDA), technical indicator creation, and uses a Random Forest model to forecast future stock prices based on historical market data.
Uber Trip Demand Analysis and Prediction using Python and Machine Learning. This project explores trip patterns, peak demand times, and uses models like Random Forest, GBRT, and XGBoost to forecast ride demand.
The project aims to provide actionable insights, such as which demographic groups purchase the most, which states and occupations contribute the highest revenue, and which product categories are most popular.
The Voice Activated System is an intelligent Python-based project designed to respond to user commands through voice input. It utilizes speech recognition and processing techniques to perform automated tasks efficiently.
📊 Amazon Sales Dashboard 2024 - Excel Project. This dashboard visualizes sales performance across different states and cities, along with product-wise insights to identify top-performing items and regions.
The dataset is stored in a PostgreSQL relational database consisting of multiple interconnected tables such as employee, customer, invoice, invoice_line, track, album, artist, and genre.
🚀E-Commerce Sales Dashboard using Power BI. I recently created this interactive dashboard to analyze E-commerce sales performance across different states, product categories, and payment modes.
The Zomato Data Analysis Project aims to explore and visualize restaurant data from the Zomato platform using Python. The project involves setting up the environment, importing essential libraries like Pandas, NumPy, Matplotlib, and Seaborn, and performing data cleaning, preparation, and analysis.
The Airbnb Price Prediction project focuses on analyzing and predicting Airbnb listing prices based on various factors such as location, amenities, room type, customer reviews, and host reputation.
This analysis aims to explore COVID-19 data in depth, examining infection rates, recovery rates, mortality trends, and the effects of various measures such as lockdowns, testing, and vaccinations.
The Telco Customer Churn dataset, the project involves collecting, cleaning, and analyzing customer data to uncover key factors influencing churn.
The project “HR Analytics – Employee Attrition Prediction” aims to predict employee attrition based on various work-related factors using the IBM HR Analytics Dataset.
Netflix offers thousands of movies and TV shows, which can make it hard for users to decide what to watch. To solve this problem, this project focuses on creating a movie recommendation system that suggests movies based on user preferences.
This project, titled “Sales Data Analysis,” focuses on analyzing Walmart’s sales dataset to derive actionable insights that can support better decision-making. the project transforms raw data into meaningful visualizations and metrics.
This project, Stock Market Analysis, aims to study historical stock price data to identify trends, patterns, and the impact of major events on stock prices. The project employs various Python libraries such as Pandas, Matplotlib, Seaborn, and yfinance to collect, clean, and visualize data.